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<p>This paper presents the comprehensive design, simulation, and experimental validation of a grid-tied hybrid renewable energy system tailored for electric vehicle (EV) charging applications. The proposed system integrates photovoltaic (PV) panels, a proton-exchange membrane fuel cell, battery storage, and a supercapacitor to ensure reliable and efficient power delivery. An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm is employed to enhance PV power extraction under dynamically varying environmental conditions. Simulation results demonstrate effective voltage boosting from 110&#xa0;V to 150&#xa0;V and a regulated output of approximately 1100&#xa0;V at 30&#xa0;A, with the PV-side current stabilized at 500&#xa0;A. The fuel cell maintains a steady output of 110&#xa0;V while its current decreases from 40&#xa0;A to 25&#xa0;A, and the battery retains a 60% state-of-charge (SOC) at 120&#xa0;V output. The hardware prototype, developed using a DSPIC30F4011 microcontroller, achieves an MPPT efficiency of 98.7%, voltage regulation within ± 1.5%, and output power deviation under 2%. Grid voltage and current waveforms exhibit low total harmonic distortion (THD), in compliance with IEEE 519 standards, with measured values of 500&#xa0;V and 13&#xa0;A, respectively. The proposed architecture offers enhanced transient response, high energy efficiency, and superior power quality, positioning it as a promising solution for next-generation smart EV charging stations.</p>

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Grid tied hybrid PV fuel cell system with energy storage and ANFIS based MPPT for smart EV charging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月28日

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  • Suresh vendoti,
  • Narasimha Prasad Tulasi,
  • Ravi Kumar Jalli,
  • Sudhakiran Ponnuru,
  • Zhang Jin,
  • P. Yakaiah,
  • Mamdooh Alwetaishi,
  • S. Prabhakar

摘要

This paper presents the comprehensive design, simulation, and experimental validation of a grid-tied hybrid renewable energy system tailored for electric vehicle (EV) charging applications. The proposed system integrates photovoltaic (PV) panels, a proton-exchange membrane fuel cell, battery storage, and a supercapacitor to ensure reliable and efficient power delivery. An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm is employed to enhance PV power extraction under dynamically varying environmental conditions. Simulation results demonstrate effective voltage boosting from 110 V to 150 V and a regulated output of approximately 1100 V at 30 A, with the PV-side current stabilized at 500 A. The fuel cell maintains a steady output of 110 V while its current decreases from 40 A to 25 A, and the battery retains a 60% state-of-charge (SOC) at 120 V output. The hardware prototype, developed using a DSPIC30F4011 microcontroller, achieves an MPPT efficiency of 98.7%, voltage regulation within ± 1.5%, and output power deviation under 2%. Grid voltage and current waveforms exhibit low total harmonic distortion (THD), in compliance with IEEE 519 standards, with measured values of 500 V and 13 A, respectively. The proposed architecture offers enhanced transient response, high energy efficiency, and superior power quality, positioning it as a promising solution for next-generation smart EV charging stations.